Off-Road Navigation of Legged Robots Using Linear Transfer Operators
Moyalan, Joseph, Zheng, Andrew, Narayanan, Sriram S. K. S, Vaidya, Umesh
–arXiv.org Artificial Intelligence
This paper presents the implementation of off-road navigation on legged robots using convex optimization through linear transfer operators. Given a traversability measure that captures the off-road environment, we lift the navigation problem into the density space using the Perron-Frobenius (P-F) operator. This allows the problem formulation to be represented as a convex optimization. Due to the operator acting on an infinite-dimensional density space, we use data collected from the terrain to get a finite-dimension approximation of the convex optimization. Results of the optimal trajectory for off-road navigation are compared with a standard iterative planner, where we show how our convex optimization generates a more traversable path for the legged robot compared to the suboptimal iterative planner.
arXiv.org Artificial Intelligence
May-4-2023
- Country:
- Asia
- Japan > Honshū
- Kantō > Tokyo Metropolis Prefecture > Tokyo (0.14)
- Middle East > Republic of Türkiye
- Karaman Province > Karaman (0.04)
- Japan > Honshū
- North America > United States
- Iowa (0.04)
- Asia
- Genre:
- Research Report (0.50)
- Technology:
- Information Technology > Artificial Intelligence > Robots > Locomotion (1.00)